MIT researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output. The advance could enhance safety and efficiency in AI-assisted decision making.

In a new paper, a team led by MIT computer scientists trained a neural network to learn NASCAR-style driving maneuvers purely from looking at a sequence of images taken from a two-person racing game. The network begins without knowing anything about cars, roads, or driving - and yet ultimately becomes able to do complex moves like overtaking an opponent on a turn and even forcing other cars off the road. 

One of the biggest challenges in computing is handling the onslaught of information while still being able to efficiently store and process it. A team from MIT CSAIL believe that the answer rests with something called “instance-optimized systems.”

CSAIL Alliances Startup Connect member Composable Analytics teams up with CheckAlt to incorporate cognitive automation to payment data capture.

In this episode of Radio Corona, we discuss digital contact tracing initiatives throughout the world with Danny Weitzner of MIT’s CSAIL, and Bobbie Johnson, a senior editor at MIT Technology Review.

The American Academy of Arts and Sciences (AAAS) announced that MIT professors Ronitt Rubinfeld and Joshua Tenenbaum were among their new 2020 members. The new class of more than 250 members recognizes the outstanding achievements of individuals in academia, the arts, business, government, and public affairs.

It can be hard to keep track of all the numbers, statistics, and charts swirling around the internet -- we’re inundated with information that can be rapidly disseminated and dissected. To carve through some of the sludge, here’s a selected highlight of recent computer science related efforts to fight COVID-19. 

MIT researchers have designed a congestion-control scheme for wireless networks that could help reduce lag times and increase quality in video streaming, video chat, mobile gaming, and other web services.